Landslide Susceptibility Mapping Using Statistical Methods along the Asian Highway, Bhutan

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14310%2F20%3A00117194" target="_blank" >RIV/00216224:14310/20:00117194 - isvavai.cz</a>

Result on the web

<a href="https://www.mdpi.com/2076-3263/10/11/430/htm" target="_blank" >https://www.mdpi.com/2076-3263/10/11/430/htm</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.3390/geosciences10110430" target="_blank" >10.3390/geosciences10110430</a>

Result language

angličtina

Original language name

Landslide Susceptibility Mapping Using Statistical Methods along the Asian Highway, Bhutan

Original language description

In areas prone to frequent landslides, the use of landslide susceptibility maps can greatly aid in the decision-making process of the socio-economic development plans of the area. Landslide susceptibility maps are generally developed using statistical methods and geographic information systems. In the present study, landslide susceptibility along road corridors was considered, since the anthropogenic impacts along a road in a mountainous country remain uniform and are mainly due to road construction. Therefore, we generated landslide susceptibility maps along 80.9 km of the Asian Highway (AH48) in Bhutan using the information value, weight of evidence, and logistic regression methods. These methods have been used independently by some researchers to produce landslide susceptibility maps, but no comparative analysis of these methods with a focus on road corridors is available. The factors contributing to landslides considered in the study are land cover, lithology, elevation, proximity to roads, drainage, and fault lines, aspect, and slope angle. The validation of the method performance was carried out by using the area under the curve of the receiver operating characteristic on training and control samples. The area under the curve values of the control samples were 0.883, 0.882, and 0.88 for the information value, weight of evidence, and logistic regression models, respectively, which indicates that all models were capable of producing reliable landslide susceptibility maps. In addition, when overlaid on the generated landslide susceptibility maps, 89.3%, 85.6%, and 72.2% of the control landslide samples were found to be in higher-susceptibility areas for the information value, weight of evidence, and logistic regression methods, respectively. From these findings, we conclude that the information value method has a better predictive performance than the other methods used in the present study. The landslide susceptibility maps produced in the study could be useful to road engineers in planning landslide prevention and mitigation works along the highway.

Czech name

—

Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

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OECD FORD branch

10500 - Earth and related environmental sciences

Project

—

Continuities

S - Specificky vyzkum na vysokych skolach<br>I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year

2020

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Geosciences

ISSN

2076-3263

e-ISSN

2076-3263

Volume of the periodical

10

Issue of the periodical within the volume

11

Country of publishing house

CH - SWITZERLAND

Number of pages

26

Pages from-to

1-26

UT code for WoS article

000593891400001

EID of the result in the Scopus database

2-s2.0-85094620030